The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
People collaborate across the world using the Internet. Especially for a large organization, it is common to include people from different backgrounds and working in different locations to bring their respective skills together. This inclusiveness has resulted in challenges that previously did not exist.
For example, a web application is accessible to users in organizations in a web browser environment. This provides the convenience of having software that is easily accessible where there is an internet connection, throughout the world. However, there are challenges when working in this environment. One common barrier is language. For example, although most users may understand a single language such as English, they are more familiar and comfortable working in another language.
Although humans and machine-assisted translation products are available to provide text in different languages, they do not completely solve the problem. Sometimes translators get it wrong. Especially for industry specific terms, it is difficult to get the proper translations that suit the specific industry. This is especially difficult when certain terms do not exist in the vocabulary of a language. For example, consider the term “sourcing.” Taken literally, sourcing may translate into “originating” or other improper translation.
Another example when translators may not work is when users or organizations have internal jargon that they prefer to more industry standard terms. For example, although the term for a person or group that handles the hiring, positioning, and overseeing of employees in an organization is commonly known in English as a “Human Resources” department, a particular organization may refer to their department as the “Human Capital Management” department or use some other term. Human Resources may be semantically accurate, but may not reflect the personalized needs of the user of organization.
Further, if a user wants to make a change, it is very inefficient. When the user sees a web page with a text element that they believe needs changing, the user will make a screen capture of the web page, note a term where the suggestion should be made, and send it to an administrator of the web application to make the suggested changes by changing one or more code elements. However, this is very cumbersome and difficult. When the administrator receives the suggestions, they are unable to see how the web page was generated. This is not as easy as finding, copying, and pasting the suggestion, since suggestions matter in their specific context. For example, the administrator cannot make the changes to all instances of web pages generated by the web application directly, since they need to find where the suggestion applies. Even though two web pages generated by the web translation application may have the same term on multiple web pages, it may not be appropriate to change it on both web pages. Some common words may have different meaning according to its use-context.